FuriosaAI is looking for a Solutions Architect to bring the full potential of our powerful RNGD chips/servers to our customers by acting as the primary technical authority in AI/LLM model deployments. From running POCs to benchmarking and debugging, you will translate RNGD’s powerful system to real-world deployments of customers’ models, empowering customers with FuriosaAI’s powerful solutions.
If you are interested in providing the technical expertise in challenging the current status-quo of AI infrastructure in real-world environments, join us in our path to a sustainable future of AI.
What You’ll DoOwn end-to-end technical enablement for US customers deploying AI models on FuriosaAI's RNGD NPU using the Furiosa SDK
Develop POCs, benchmarking studies, and live debugging sessions directly in customer environments
Act as the technical authority to the US BD/Sales team during pre-sales and enterprise evaluations; translate deep technical capability into business value for engineering and C-suite audiences
Develop deep, current expertise in FuriosaAI's hardware and software stack and demonstrate it at US technical forums, AI conferences, and customer workshops
Onboard and train customers on integration patterns, optimization workflows, and best practices post-purchase
Serve as a technical feedback loop from US customers back to Seoul HQ product and engineering teams
2–5 years in a US customer-facing technical role: Solutions Architect, Sales Engineer, Forward Deployed Engineer, or equivalent at an AI infra, cloud, or semiconductor company
Actively current on the AI/LLM landscape — tracking model releases, inference frameworks, and serving stack evolution in real time
Hands-on experience with modern inference stacks: vLLM, SGLang, TensorRT-LLM, Triton Inference Server, or similar
Hands-on experience with agent and orchestration frameworks: LangChain, LlamaIndex, LangGraph, AutoGen, or MCP-based tooling
Proficiency in Python; comfortable with DNN frameworks (PyTorch, TensorFlow)
Strong written and verbal communication — able to engage credibly with ML engineers at frontier labs and VP/C-suite executives
Authorized to work in the US; able to travel to customer sites and to Seoul HQ periodically
Prior experience at a US AI chip company, cloud silicon team, or AI infrastructure startup
Familiarity with NPU/GPU accelerator ecosystems, PCIe integration, and data center hardware deployment
Experience with inference optimization: quantization, kernel tuning, batching strategies, memory bandwidth optimization
Proficiency in C, C++, or Rust
Experience working with distributed or cross-timezone engineering teams
Skills Required
- 2-5 years in a US customer-facing technical role
- Hands-on experience with modern inference stacks
- Proficiency in Python
- Strong written and verbal communication
- Authorized to work in the US
What We Do
FuriosaAI designs and develops data center accelerators for the most advanced AI models and applications. Our mission is to make AI computing sustainable so everyone on Earth has access to powerful AI. Our Background Three misfit engineers with each from HW, SW and algorithm fields who had previously worked for AMD, Qualcomm and Samsung got together and founded FuriosaAI in 2017 to build the world’s best AI chips. The company has raised more than $100 million, with investments from DSC Investment, Korea Development Bank, and Naver, the largest internet provider in Korea. We have partnered on our first two products with a wide range of industry leaders including TSMC, ASUS, SK Hynix, GUC, and Samsung. FuriosaAI now has over 140 employees across Seoul, Silicon Valley, and Europe. Our Approach We are building full stack solutions to offer the most optimal combination of programmability, efficiency, and ease of use. We achieve this through a “first principles” approach to engineering: We start with the core problem, which is how to accelerate.
